entropy_disc

Models for non-linear time series analysis and causality detection. The main functionalities of this package consist of an implementation of the classical causality test (C.W.J.Granger 1980) <doi:10.1016/0165-1889(80)90069-X>, and a non-linear version of it based on feed-forward neural networks. This package contains also an implementation of the Transfer Entropy <doi:10.1103/PhysRevLett.85.461>, and the continuous Transfer Entropy using an approximation based on the k-nearest neighbors <doi:10.1103/PhysRevE.69.066138>. There are also some other useful tools, like the VARNN (Vector Auto-Regressive Neural Network) prediction model, the Augmented test of stationarity, and the discrete and continuous entropy and mutual information.

Youssef Hmamouche

NlinTS

Models for Non Linear Causality Detection in Time Series

entropy_disc function

<dl><dt>V</dt>
<dd>Integer vector.</dd>
<dt>log</dt>
<dd>String argument in the set ("log2", "loge","log10"), which indicates the log function to use. The log2 is used by default.</dd></dl>

Arguments

Discrete Entropy — entropy_disc

<dl>

<dt>V</dt>
<dd>Integer vector.</dd>


<dt>log</dt>
<dd>String argument in the set ("log2", "loge","log10"), which indicates the log function to use. The log2 is used by default.</dd>

</dl>

entropy_disc: Discrete Entropy

Description

Usage

Arguments

Details

Examples